期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 68, 期 7, 页码 7136-7149出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2919915
关键词
Computation offloading; fog radio access networks; resource allocation
资金
- Beijing Natural Science Foundation [L182039]
- National Science and Technology Major Project [2017ZX03001014]
- UKEPSRC [EP/N005597/2]
- NSFC [61728101]
- H2020-MSCA-RISE-2015 [690750]
- SUTD-ZJU Research Collaboration [SUTD-ZJU/RES/01/2016, SUTD-ZJU/RES/05/2016]
- EPSRC [EP/N005597/2] Funding Source: UKRI
Based on a hierarchical cloud-fog computing-enabled paradigm, fog radio access networks (F-RANs) can provide abundant resource to support the future mobile artificial intelligent services. However, due to the differences of computation and communication capabilities at the cloud computing center, the fog computing based access points (F-APs), and the user devices, it is challenging to propose efficient computation offloading strategies to fully explore the potential of F-RANs. In this paper, we study the design of computation offloading in F-RANs to minimize the total cost with respect to the energy consumption and the offloading latency. In particular, a joint optimization problem is formulated to optimize the offloading decision, the computation and the radio resources allocation. To solve this non-linear and non-convex problem, an iterative algorithm is designed, which can be proved to converge a stationary optimal solution with polynomial computational complexity. Finally, the simulation results are provided to show the performance gains of our proposed joint optimization algorithm.
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